package com.yupi.yuaiagent.app;

import com.yupi.yuaiagent.advisor.MyLoggerAdvisor;
import com.yupi.yuaiagent.advisor.ReReadingAdvisor;
import com.yupi.yuaiagent.advisor.SensitiveWordAdvisor;
import com.yupi.yuaiagent.chatmemory.FileBasedChatMemory;
import com.yupi.yuaiagent.demo.rag.QueryRewriter;
import com.yupi.yuaiagent.rag.LoveAppRagCustomAdvisorFactory;
import jakarta.annotation.Resource;
import lombok.extern.slf4j.Slf4j;
import org.springframework.ai.chat.client.ChatClient;
import org.springframework.ai.chat.client.advisor.MessageChatMemoryAdvisor;
import org.springframework.ai.chat.client.advisor.QuestionAnswerAdvisor;
import org.springframework.ai.chat.client.advisor.api.Advisor;
import org.springframework.ai.chat.memory.ChatMemory;
import org.springframework.ai.chat.memory.InMemoryChatMemory;
import org.springframework.ai.chat.messages.AssistantMessage;
import org.springframework.ai.chat.model.ChatModel;
import org.springframework.ai.chat.model.ChatResponse;
import org.springframework.ai.mcp.AsyncMcpToolCallbackProvider;
import org.springframework.ai.tool.ToolCallback;
import org.springframework.ai.tool.ToolCallbackProvider;
import org.springframework.ai.vectorstore.VectorStore;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.stereotype.Component;
import reactor.core.publisher.Flux;

import java.util.List;

import static org.springframework.ai.chat.client.advisor.AbstractChatMemoryAdvisor.CHAT_MEMORY_CONVERSATION_ID_KEY;
import static org.springframework.ai.chat.client.advisor.AbstractChatMemoryAdvisor.CHAT_MEMORY_RETRIEVE_SIZE_KEY;

/**
 * @className: LoveApp
 * @author: xxy-Rain
 * @date: 2025/10/19 14:48
 * @version: 1.0
 * @description: TODO
 */
@Component
@Slf4j
public class LoveApp {

    private final ChatClient chatClient;

    public static final String SYSTEM_PROMPT = "扮演深耕恋爱心理领域的专家。开场向用户表明身份，告知用户可倾诉恋爱难题。" +
            "围绕单身、恋爱、已婚三种状态提问：单身状态询问社交圈拓展及追求心仪对象的困扰；恋爱状态询问沟通、习惯差异引发的矛盾；" +
            "已婚状态询问家庭责任与亲属关系处理的问题。引导用户详述事情经过、对方反应及自身想法，" +
            "以便给出专属解决方案。";

    /**
     * 初始化AI客户端
     * @param dashscopeChatModel
     */
    public LoveApp(ChatModel dashscopeChatModel) {
        //初始化基于文件的对话记忆
        String fileDir = System.getProperty("user.dir") + "/tmp/chat-memory";
        ChatMemory chatMemory = new FileBasedChatMemory(fileDir);
        //初始化基于内存的对话记忆
        //ChatMemory chatMemory = new InMemoryChatMemory();
        chatClient = ChatClient.builder(dashscopeChatModel)
                .defaultSystem(SYSTEM_PROMPT) //系统预设
                .defaultAdvisors(
                        new MessageChatMemoryAdvisor(chatMemory) ,
                        //自定义日志Advisor,可按需开启
                        new MyLoggerAdvisor(),
                        //自定义推理增强Advisor，可以按需开启，但他会花更多token
                        new ReReadingAdvisor()
                )
                .build();
    }

    /**
     * AI基础对话，支持多轮对话记忆
     * @param message
     * @param chatId
     * @return
     */
    public String doChat(String message,String chatId){
        ChatResponse chatResponse = chatClient
                .prompt()
                .user(message)
                .advisors(spec -> spec.param(CHAT_MEMORY_CONVERSATION_ID_KEY, chatId)
                        .param(CHAT_MEMORY_RETRIEVE_SIZE_KEY, 10)) //对话轮数
                .call()
                .chatResponse();
        String content = chatResponse.getResult().getOutput().getText();
        log.info("content:{}",content);
        return content;
    }

    /**
     * AI基础对话，支持多轮对话记忆,SSE流式传输
     * @param message
     * @param chatId
     * @return
     */
    public Flux<String> doChatByStream(String message, String chatId){
        return chatClient
                .prompt()
                .user(message)
                .advisors(spec -> spec.param(CHAT_MEMORY_CONVERSATION_ID_KEY, chatId)
                        .param(CHAT_MEMORY_RETRIEVE_SIZE_KEY, 10)) //对话轮数
                .stream()
                .content();
    }

    record LoveReport(String title, List<String> suggestions){

    }

    /**
     * AI恋爱报告功能演示格式化输出
     * @param message
     * @param chatId
     * @return
     */
    public LoveReport doChatWithReport(String message,String chatId){
        LoveReport loveReport = chatClient
                .prompt()
                .system(SYSTEM_PROMPT + "每次对话后都要生成恋爱结果，标题为{用户名}的恋爱报告，内容为建议列表")
                .user(message)
                .advisors(spec -> spec.param(CHAT_MEMORY_CONVERSATION_ID_KEY, chatId)
                        .param(CHAT_MEMORY_RETRIEVE_SIZE_KEY, 10)) //对话轮数
                .call()
                .entity(LoveReport.class);
        log.info("loveReport:{}",loveReport);
        return loveReport;
    }

    //AI恋爱知识库温问答功能
    @Resource
    private VectorStore loveAppVectorStore;

    @Resource
    private Advisor loveAppRagCloudAdvisor;

    @Resource
    private VectorStore pgVectorVectorStore;

    @Resource
    private QueryRewriter queryRewriter;

    /**
     * 和RAG知识库对话
     * @param message
     * @param chatId
     * @return
     */
    public String doChatWithRag(String message,String chatId){
        //查询重写
        String rewrittenMessage = queryRewriter.doQueryRewrite(message);
        ChatResponse chatResponse = chatClient.prompt()
                //使用改写后的查询
                .user(rewrittenMessage)
                .advisors(
                        spec -> spec.param(CHAT_MEMORY_CONVERSATION_ID_KEY, chatId)
                                .param(CHAT_MEMORY_RETRIEVE_SIZE_KEY, 10))
                //开启日志
                .advisors(new MyLoggerAdvisor())
                //应用RAG检索增强服务 基于内存
                //.advisors(new QuestionAnswerAdvisor(loveAppVectorStore))

                //应用RAG检索增强服务 基于云知识库
                .advisors(loveAppRagCloudAdvisor)

                //应用RAG检索增强服务，基于PgVector向量存储
                //.advisors(new QuestionAnswerAdvisor(pgVectorVectorStore))
                //应用自定义RAG检索增强服务
//                .advisors(
//                        LoveAppRagCustomAdvisorFactory.createLoveAppRagCustomAdvisor(
//                                loveAppVectorStore,"单身"
//                        )
//                )
                .call()
                .chatResponse();
        String output = chatResponse.getResult().getOutput().getText();
        log.info("content:{}",output);
        return output;
    }

    //AI恋爱知识库调用工具
    @Resource
    private ToolCallback[] allTools;

    /**
     * AI恋爱报告功能，支持调用工具
     * @param message
     * @param chatId
     * @return
     */
    public String doChatWithTools(String message,String chatId){
        ChatResponse chatResponse = chatClient
                .prompt()
                .user(message)
                .advisors(spec -> spec.param(CHAT_MEMORY_CONVERSATION_ID_KEY, chatId)
                        .param(CHAT_MEMORY_RETRIEVE_SIZE_KEY, 10)) //对话轮数
                .advisors(new MyLoggerAdvisor())
                .tools(allTools)
                .call()
                .chatResponse();
        String content = chatResponse.getResult().getOutput().toString();
        log.info("content:{}",content);
        return content;
    }

    //AI调用MCP服务
    @Resource
    private ToolCallbackProvider toolCallbackProvider;

    /**
     * AI恋爱报告功能（调用MCP服务）
     * @param message
     * @param chatId
     * @return
     */
    public String doChatWithMcp(String message,String chatId){
        ChatResponse chatResponse = chatClient
                .prompt()
                .user(message)
                .advisors(spec -> spec.param(CHAT_MEMORY_CONVERSATION_ID_KEY, chatId)
                        .param(CHAT_MEMORY_RETRIEVE_SIZE_KEY, 10)) //对话轮数
                .advisors(new MyLoggerAdvisor())
                .tools(toolCallbackProvider)
                .call()
                .chatResponse();
         String content = chatResponse.getResult().getOutput().toString();
        log.info("content:{}",content);
        return content;
    }

}
